Feature Detection is an important step in all major machine vision applications. Feature points are important in tracking objects between frames and finding correspondence between 2 or more images. One known technique for corner detection is FAST algorithm proposed in E. Rosten and T. Drummond. “Machine Learning for High-Speed Corner Detection”, Computer Vision ECCV 2006, Lecture Notes in Computer Science, Volume 3951, 2006, pages 430 to 443.
Given the importance of Feature Detection in vision applications and FAST being a popular feature point detection algorithm, any hardware system capable of solving machine vision tasks should be capable of providing high performance for FAST algorithm. Machine vision algorithms typically involve similar computation tasks across image blocks or across the entire image and also need to operate at high frame rate per second (fps). Vector SIMD engines are well suited for machine vision tasks. The data overlap that typically occurs in machine vision kernels can be effectively exploited by a vector SIMD engine for better performance compared to a scalar engine.